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Date: Wed, 7 Feb 2024 16:17:04 -0300 Subject: GLPK doubt To: help-glpk@gnu.org From: Nicolas Herculano Pires <rgm47...@comp.uems.br> > Dear esteemed GNU colleague, > > I hope this message finds you well. I am writing to address an issue I > have encountered with GLPK, albeit it may seem trivial, it remains a > pertinent concern. I am currently grappling with GLPK in the context > of solving an optimization problem, specifically pertaining to > portfolio project selection and scheduling. > > My dilemma lies in the utilization of GLPK without employing decision > variables. Allow me to elucidate further: I am employing GLPK to > tackle a portfolio project selection conundrum encompassing 200 > projects over a planning horizon of 60 months. However, I have been > unable to find any resources or documentation on how to utilize GLPK > without employing decision variables. > > You may wonder, "What is the significance of reducing these variables > through GLPK?" The essence of my inquiry lies in the potential > reduction of variables. To illustrate, envision a scenario where each > of the 60 columns represents a month, and among these, only one column > is selected per project. This leaves the remaining 59 columns > redundant. Consequently, would it not be more efficient to represent > the selected month with a single indicator column, rather than > allocating separate columns for each month? > > For instance, if GLPK selects column 30 (corresponding to month 30), > the preceding columns (1 to 29) and subsequent columns (31 to 60) > would inherently hold values of zero, rendering them unnecessary. > Therefore, it seems logical to streamline the representation by > condensing the 60 columns into a single indicator column denoting the > selected month. > > One might inquire, "But what if no month is selected?" In such > instances, I propose to designate a value of zero to indicate the > absence of a selected month, effectively reducing the total number of > variables from 12,000 to a mere 200. > > I am keen to explore any insights or guidance you may provide on this > matter. Your expertise and assistance in optimizing the utilization of > GLPK would be immensely appreciated. > > Warm regards, > Nícolas Herculano >
